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dvc/dvc/api/show.py
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skshetry f2673acb53 metrics/params: support reading from cached files and directories, use repo-relative path consistently (#9909) 
* metrics

* fix path handling

* fix dvc metrics diff

* params show/diff

* share common utils

* remove onerror_collect from exp_show

* extract read_params

* move around code

* fix path handling on Windows

* rename _show to _gather_metrics

* remove _collect_vars

* add tests

* Revert "remove _collect_vars"

This reverts commit 6d2cb500c32a882497406d66fb13e613790c3436.

* bring back _collect_vars

* fix tests

* fix paths
2023-09-11 17:41:37 +05:45

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import typing
from collections import Counter
from typing import Dict, Iterable, Optional, Union
from funcy import first
from dvc.repo import Repo
def _postprocess(results):
processed: Dict[str, Dict] = {}
for rev, rev_data in results.items():
if not rev_data:
continue
processed[rev] = {}
counts: typing.Counter[str] = Counter()
for file_data in rev_data["data"].values():
for k in file_data["data"]:
counts[k] += 1
for file_name, file_data in rev_data["data"].items():
to_merge = {
(k if counts[k] == 1 else f"{file_name}:{k}"): v
for k, v in file_data["data"].items()
}
processed[rev] = {**processed[rev], **to_merge}
if "workspace" in processed:
del processed["workspace"]
return processed
def metrics_show(
*targets: str,
repo: Optional[str] = None,
rev: Optional[str] = None,
config: Optional[Dict] = None,
) -> Dict:
"""Get metrics tracked in `repo`.
Without arguments, this function will retrieve all metrics from all tracked
metric files, for the current working tree.
See the options below to restrict the metrics retrieved.
Args:
*targets (str, optional): Names of the metric files to retrieve
metrics from. For example, "classifier_eval.json,
clustering_eval.json".
If no `targets` are provided, all metric files tracked in `dvc.yaml`
will be used.
Note that targets don't necessarily have to be defined in `dvc.yaml`.
repo (str, optional): Location of the DVC repository.
Defaults to the current project (found by walking up from the
current working directory tree).
It can be a URL or a file system path.
Both HTTP and SSH protocols are supported for online Git repos
(e.g. [user@]server:project.git).
rev (str, optional): Name of the `Git revision`_ to retrieve metrics
from.
Defaults to `None`.
An example of git revision can be a branch or tag name, a commit
hash or a dvc experiment name.
If `repo` is not a Git repo, this option is ignored.
If `None`, the current working tree will be used.
config (dict, optional): config to be passed through to DVC project.
Defaults to `None`.
Returns:
Dict: See Examples below.
Examples:
- No arguments.
Working on https://github.com/iterative/example-get-started
>>> import dvc.api
>>> metrics = dvc.api.metrics_show()
>>> print(json.dumps(metrics, indent=4))
{
"avg_prec": 0.9249974999612706,
"roc_auc": 0.9460213440787918
}
---
- Using `rev`.
Working on https://github.com/iterative/example-get-started
>>> import json
>>> import dvc.api
>>> metrics = dvc.api.metrics_show(rev="tune-hyperparams")
>>> print(json.dumps(metrics, indent=4))
{
"avg_prec": 0.9268792615819422,
"roc_auc": 0.945093365854111
}
---
- Using `targets`.
Working on https://github.com/iterative/example-get-started
>>> import json
>>> import dvc.api
>>> metrics = dvc.api.metrics_show("evaluation.json")
>>> print(json.dumps(metrics, indent=4))
{
"avg_prec": 0.9249974999612706,
"roc_auc": 0.9460213440787918
}
---
- Git URL as `repo`.
>>> import json
>>> import dvc.api
>>> metrics = dvc.api.metrics_show(
... repo="https://github.com/iterative/demo-fashion-mnist")
>>> print(json.dumps(metrics, indent=4))
{
"loss": 0.25284987688064575,
"accuracy": 0.9071000218391418
}
.. _Git revision:
https://git-scm.com/docs/revisions
"""
from dvc.repo.metrics.show import to_relpath
with Repo.open(repo, config=config) as _repo:
metrics = _repo.metrics.show(
targets=targets,
revs=rev if rev is None else [rev],
on_error="raise",
)
metrics = {
k: to_relpath(_repo.fs, _repo.root_dir, v) for k, v in metrics.items()
}
metrics = _postprocess(metrics)
if not metrics:
return {}
return metrics[first(metrics)]
def params_show(
*targets: str,
repo: Optional[str] = None,
stages: Optional[Union[str, Iterable[str]]] = None,
rev: Optional[str] = None,
deps: bool = False,
config: Optional[Dict] = None,
) -> Dict:
"""Get parameters tracked in `repo`.
Without arguments, this function will retrieve all params from all tracked
parameter files, for the current working tree.
See the options below to restrict the parameters retrieved.
Args:
*targets (str, optional): Names of the parameter files to retrieve
params from. For example, "params.py, myparams.toml".
If no `targets` are provided, all parameter files tracked in `dvc.yaml`
will be used.
Note that targets don't necessarily have to be defined in `dvc.yaml`.
repo (str, optional): location of the DVC repository.
Defaults to the current project (found by walking up from the
current working directory tree).
It can be a URL or a file system path.
Both HTTP and SSH protocols are supported for online Git repos
(e.g. [user@]server:project.git).
stages (Union[str, Iterable[str]], optional): Name or names of the
stages to retrieve parameters from.
Defaults to `None`.
If `None`, all parameters from all stages will be retrieved.
If this method is called from a different location to the one where
the `dvc.yaml` is found, the relative path to the `dvc.yaml` must
be provided as a prefix with the syntax `{relpath}:{stage}`.
For example: `subdir/dvc.yaml:stage-0` or `../dvc.yaml:stage-1`.
rev (str, optional): Name of the `Git revision`_ to retrieve parameters
from.
Defaults to `None`.
An example of git revision can be a branch or tag name, a commit
hash or a dvc experiment name.
If `repo` is not a Git repo, this option is ignored.
If `None`, the current working tree will be used.
deps (bool, optional): Whether to retrieve only parameters that are
stage dependencies or not.
Defaults to `False`.
config (dict, optional): config to be passed through to DVC project.
Defaults to `None`.
Returns:
Dict: See Examples below.
Examples:
- No arguments.
Working on https://github.com/iterative/example-get-started
>>> import json
>>> import dvc.api
>>> params = dvc.api.params_show()
>>> print(json.dumps(params, indent=4))
{
"prepare": {
"split": 0.2,
"seed": 20170428
},
"featurize": {
"max_features": 200,
"ngrams": 2
},
"train": {
"seed": 20170428,
"n_est": 50,
"min_split": 0.01
}
}
---
- Filtering with `stages`.
Working on https://github.com/iterative/example-get-started
`stages` can a single string:
>>> import json
>>> import dvc.api
>>> params = dvc.api.params_show(stages="prepare")
>>> print(json.dumps(params, indent=4))
{
"prepare": {
"split": 0.2,
"seed": 20170428
}
}
Or an iterable of strings:
>>> import json
>>> import dvc.api
>>> params = dvc.api.params_show(stages=["prepare", "train"])
>>> print(json.dumps(params, indent=4))
{
"prepare": {
"split": 0.2,
"seed": 20170428
},
"train": {
"seed": 20170428,
"n_est": 50,
"min_split": 0.01
}
}
---
- Using `rev`.
Working on https://github.com/iterative/example-get-started
>>> import json
>>> import dvc.api
>>> params = dvc.api.params_show(rev="tune-hyperparams")
>>> print(json.dumps(params, indent=4))
{
"prepare": {
"split": 0.2,
"seed": 20170428
},
"featurize": {
"max_features": 200,
"ngrams": 2
},
"train": {
"seed": 20170428,
"n_est": 100,
"min_split": 8
}
}
---
- Using `targets`.
Working on `multi-params-files` folder of
https://github.com/iterative/pipeline-conifguration
You can pass a single target:
>>> import json
>>> import dvc.api
>>> params = dvc.api.params_show("params.yaml")
>>> print(json.dumps(params, indent=4))
{
"run_mode": "prod",
"configs": {
"dev": "configs/params_dev.yaml",
"test": "configs/params_test.yaml",
"prod": "configs/params_prod.yaml"
},
"evaluate": {
"dataset": "micro",
"size": 5000,
"metrics": ["f1", "roc-auc"],
"metrics_file": "reports/metrics.json",
"plots_cm": "reports/plot_confusion_matrix.png"
}
}
Or multiple targets:
>>> import json
>>> import dvc.api
>>> params = dvc.api.params_show(
... "configs/params_dev.yaml", "configs/params_prod.yaml")
>>> print(json.dumps(params, indent=4))
{
"configs/params_prod.yaml:run_mode": "prod",
"configs/params_prod.yaml:config_file": "configs/params_prod.yaml",
"configs/params_prod.yaml:data_load": {
"dataset": "large",
"sampling": {
"enable": true,
"size": 50000
}
},
"configs/params_prod.yaml:train": {
"epochs": 1000
},
"configs/params_dev.yaml:run_mode": "dev",
"configs/params_dev.yaml:config_file": "configs/params_dev.yaml",
"configs/params_dev.yaml:data_load": {
"dataset": "development",
"sampling": {
"enable": true,
"size": 1000
}
},
"configs/params_dev.yaml:train": {
"epochs": 10
}
}
---
- Git URL as `repo`.
>>> import json
>>> import dvc.api
>>> params = dvc.api.params_show(
... repo="https://github.com/iterative/demo-fashion-mnist")
{
"train": {
"batch_size": 128,
"hidden_units": 64,
"dropout": 0.4,
"num_epochs": 10,
"lr": 0.001,
"conv_activation": "relu"
}
}
.. _Git revision:
https://git-scm.com/docs/revisions
"""
from dvc.repo.metrics.show import to_relpath
if isinstance(stages, str):
stages = [stages]
with Repo.open(repo, config=config) as _repo:
params = _repo.params.show(
revs=rev if rev is None else [rev],
targets=targets,
deps_only=deps,
on_error="raise",
stages=stages,
)
params = {k: to_relpath(_repo.fs, _repo.root_dir, v) for k, v in params.items()}
params = _postprocess(params)
if not params:
return {}
return params[first(params)]
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